scholarly journals A Potential ceRNA Network for Neurological Damage in Preterm Infants

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jin Huang ◽  
Xuejing Liang ◽  
Zhenyu Cai
Keyword(s):  
Brain Injury ◽  
Preterm Infants ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Neurological Injury ◽  
Ppi Network ◽  
Neurological Damage ◽  
Injury Group ◽  
Differentially Expressed Mirnas ◽  
Geo Database

Objective. This study is aimed at identifying key genes involved in neurological damage in preterm infants and at determining their potential circRNA-miRNA-mRNA regulatory mechanisms. Methods. Differentially expressed miRNAs, mRNAs, and circRNAs were downloaded from the GEO database. GO and KEGG enrichment analyses were used to determine possible relevant functions of differentially expressed mRNAs. The TTRUST database was used to predict differential TF-mRNA regulatory relationships. Then, CircMIR, miRDB, TargetScan and miRTarBase were then used to map circRNA/miRNA-TF/mRNA interaction networks. Finally, GSEA enrichment analysis was performed on the core transcription factors. Results. A total of 640 mRNAs, 139 circRNAs, and 206 differentially expressed miRNAs associated with neurological injury in preterm infants were obtained. Based on the findings of Cytoscape and PPI network analysis, the hsa_circ_0008439-hsa-mir-3665-STAT3-MMP3 regulatory axis was established. GSEA analysis revealed that suppressed expression levels of STAT3 were associated with upregulated oxidative phosphorylation pathways in the neurological injury group of preterm infants. Conclusions. The circRNA-miRNA-TF-mRNA regulatory network of neurological injury in preterm infants can be used to elucidate on the pathogenesis of brain injury and help us with the early detection of brain injury in preterm infants.

scholarly journals Screening and Analysis of Key Genes in miRNA-mRNA Regulatory Network of Membranous Nephropathy

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yawei Hou ◽  
Yameng Li ◽  
Yichuan Wang ◽  
Wenpu Li ◽  
Zhenwei Xiao
Keyword(s):  
Membranous Nephropathy ◽  
Regulatory Network ◽  
Target Genes ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Data Set ◽  
Downstream Target ◽  
Differentially Expressed Mirnas ◽  
Candidate Target ◽  
Geo Database

Background. MicroRNAs (miRNAs) are confirmed to participate in occurrence, development, and prevention of membranous nephropathy (MN), but their mechanism of action is unclear. Objective. With the GEO database and the use of bioinformatics, miRNA-mRNA regulatory network genes relevant to MN were explored and their potential mechanism of action was explained. Methods. The MN-related miRNA chip data set (GSE51674) and mRNA chip data set (GSE108109) were downloaded from the GEO database. Differential analysis was performed using the GEO2R online tool. TargetScan, miRTarBase, and StarBase databases were used to predict potential downstream target genes regulated by differentially expressed miRNAs, and the intersection with differential genes were taken to obtain candidate target genes. According to the regulatory relationship between miRNA and mRNA, the miRNA-mRNA relationship pair was clarified and Cytoscape was used to construct a miRNA-mRNA regulatory network. WebGestalt was used to conduct enrichment analysis of the biological process of differential mRNAs in the regulatory network; FunRich analyzes the differential mRNA pathways in the miRNA-mRNA regulatory network. And the STRING database was used to construct a PPI network for candidate target genes, and Cytoscape visually analyzes the PPI network. Results. Experiments were conducted to screen differentially expressed miRNAs and mRNAs. There were 30 differentially expressed miRNAs, including 22 upregulated and 8 downregulated; and 1267 differentially expressed mRNAs, including 536 upregulated and 731 downregulated. Using TargetScan, miRTarBase, and StarBase databases to predict the downstream targets of differentially expressed miRNAs, 2957 downstream target genes coexisting in the 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 175 candidate target genes. Finally, 36 miRNA-mRNA relationship pairs comprising 10 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out, and the regulatory network was constructed. Further analysis revealed that the miRNA regulatory network genes may be involved in the development of membranous nephropathy by mTOR, PDGFR-β, LKB1, and VEGF/VEGFR signaling pathways. Conclusion. The miRNA regulatory network genes may participate in the regulation of podocyte autophagy, lipid metabolism, and renal fibrosis through mTOR, PDGFR-β, LKB1, and VEGF/VEGFR signaling pathways, thereby affecting the occurrence and development of membranous nephropathy.

Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

2021 ◽  
Vol 15 (8) ◽  
pp. 927-936 ◽  
Author(s):  
Yan Peng ◽  
Yuewu Liu ◽  
Xinbo Chen
Keyword(s):  
Drought Stress ◽  
Target Genes ◽  
Hot Spot ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Promising Tool ◽  
Differentially Expressed Mirnas ◽  
Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identified. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

scholarly journals MicroRNA expression profiling involved in Borax-induced anti-tumor effect using gene-chip analysis

2020 ◽  
Author(s):  
Lun Wu ◽  
Ying Wei ◽  
Wen-Bo Zhou ◽  
Jiao Zhou ◽  
Li-Hua Yang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Hepg2 Cells ◽  
Enrichment Analysis ◽  
Gene Chip ◽  
Differentially Expressed ◽  
Control Group ◽  
Pathway Enrichment Analysis ◽  
Ras Signaling ◽  
Therapeutic Benefits ◽  
Differentially Expressed Mirnas

Abstract Background Borax, a boron compound, which is becoming widely recognized for its biological effects, including antioxidant activity, cytotoxicity, and potential therapeutic benefits. However, the specific molecular mechanisms underlying borax-induced anti-tumor effect still remain to be to further elucidated. MicroRNAs (miRNAs) may play key roles in cellular processes including tumor progression, cell apoptosis and cytotoxicity. Thus, this study aimed to investigate, whether miRNAs were involved in the borax-mediated anti-tumor effect using miRNA profiling of a human liver cancer cell line (HepG2) using gene-chip analysis.Methods Total RNA was extracted and purified from HepG2 cells that were treated with 4 mM borax for either 2 or 24 h. The samples underwent microarray analysis using an Agilent Human miRNA Array. Differentially expressed miRNAs were analysed by volcano plot and heatmap, and were validated using real-time fluorescent quantitative PCR (qPCR).ResultsAmong this, 2- or 24-h exposure to borax significantly altered the expression level of miRNAs in HepG2 cells, 4 or 14 were upregulated and 3 were downregulated compared with the control group, respectively (≥2-fold; P<0.05). GO enrichment analysis and KEGG pathway enrichment analysis revealed that target genes of differentially expressed miRNAs in HepG2 cells predominantly participated in MAPK signaling pathway, TGF-beta signaling pathway, NF-kappa B signaling pathway, etc; in 2-h borax treatment group, while Ras signaling pathway, FoxO signaling pathway, Cellular senescence, etc; involved in 24-h treatment group.Conclusions Result indicates that borax-induced anti-tumor effect may be associated with alterations in miRNAs.

scholarly journals Identification of Potential Therapeutic Targets and Molecular Regulatory Mechanisms for Osteoporosis by Bioinformatics Methods

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Li Zhang ◽  
Yunlong Yang ◽  
Dechun Geng ◽  
Yonghua Wu
Keyword(s):  
Immune Cell ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Differential Analysis ◽  
Ppi Network ◽  
The Difference ◽  
And Control

Background. Osteoporosis is characterized by low bone mass, deterioration of bone tissue structure, and susceptibility to fracture. New and more suitable therapeutic targets need to be discovered. Methods. We collected osteoporosis-related datasets (GSE56815, GSE99624, and GSE63446). The methylation markers were obtained by differential analysis. Degree, DMNC, MCC, and MNC plug-ins were used to screen the important methylation markers in PPI network, then enrichment analysis was performed. ROC curve was used to evaluate the diagnostic effect of osteoporosis. In addition, we evaluated the difference in immune cell infiltration between osteoporotic patients and control by ssGSEA. Finally, differential miRNAs in osteoporosis were used to predict the regulators of key methylation markers. Results. A total of 2351 differentially expressed genes and 5246 differentially methylated positions were obtained between osteoporotic patients and controls. We identified 19 methylation markers by PPI network. They were mainly involved in biological functions and signaling pathways such as apoptosis and immune inflammation. HIST1H3G, MAP3K5, NOP2, OXA1L, and ZFPM2 with higher AUC values were considered key methylation markers. There were significant differences in immune cell infiltration between osteoporotic patients and controls, especially dendritic cells and natural killer cells. The correlation between MAP3K5 and immune cells was high, and its differential expression was also validated by other two datasets. In addition, NOP2 was predicted to be regulated by differentially expressed hsa-miR-3130-5p. Conclusion. Our efforts aim to provide new methylation markers as therapeutic targets for osteoporosis to better treat osteoporosis in the future.

scholarly journals Identifcation of The Ferroptosis-Related Gene Signature In Placenta of Patients With Early-Onset Preeclampsia

2021 ◽  
Author(s):  
Nana Yang ◽  
Qianghua Wang ◽  
Biao Ding ◽  
Yinging Gong ◽  
Yue Wu ◽  
...  
Keyword(s):  
Iron Homeostasis ◽  
Molecular Mechanisms ◽  
Late Onset ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Network Analyses

Abstract Background: The accumulation of ROS resulting from upregulated levels of oxidative stress is commonly implicated in preeclampsia (PE). Ferroptosis is a novel form of iron-dependent cell death instigated by lipid peroxidation likely plays important role in PE pathogenesis. This study aims to investigate expression profiles and functions of the ferroptosis-related genes (FRGs) in early- and late-onset preeclampsia.Methods: The gene expression data and clinical information were downloaded from GEO database. The “limma” R package was used for screening differentially expressed genes. GO(Gene Ontology), Kyoto Encyclopedia of Genes and Genomes(KEGG) and protein protein interaction (PPI) network analyses were conducted to investigate the bioinformatics functions and molecular interactions of significantly different FRGs. Quantitative real-time reverse transcriptase PCR was used to verify the expression of hub FRGs in PE.Results: A total number of 4,215 DEGs were identified between EOPE and preterm cases and 3,356 DEGs were found between EOPE and LOPE subtypes. 20 significantly different FRGs were identified in EOPE, while only 3 in LOPE. Functional enrichment analysis revealed that the differentially expressed FRGs was mainly involved in EOPE and enriched in hypoxia- and iron-related pathways, such as response to hypoxia, iron homeostasis and iron ion binding process. The PPI network analysis and verification by RT-qPCR resulted in the identification of the following six interesting FRGs: FTH1, HIF1A, FTL, IREB2, MAPK8 and PLIN2. Conclusions: EOPE and LOPE owned distinct underlying molecular mechanisms and ferroptosis may be mainly implicated in pathogenesis of EOPE. Further studies are necessary for deeper inquiry into placental ferroptosis and its role in the pathogenesis of EOPE.

scholarly journals Identification of microRNAs and genes as biomarkers of atrial fibrillation using a bioinformatics approach

2019 ◽  
Vol 47 (8) ◽  
pp. 3580-3589 ◽  
Author(s):  
Yingyuan Li ◽  
Wulin Tan ◽  
Fang Ye ◽  
Faling Xue ◽  
Shaowei Gao ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Control Groups ◽  
Protein Protein Interaction ◽  
Differentially Expressed Mirnas ◽  
Software Modules ◽  
And Control

Objective We aimed to explore potential microRNAs (miRNAs) and target genes related to atrial fibrillation (AF). Methods Data for microarrays GSE70887 and GSE68475, both of which include AF and control groups, were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs between AF and control groups were identified within each microarray, and the intersection of these two sets was obtained. These miRNAs were mapped to target genes in the miRNet database. Functional annotation and enrichment analysis of these target genes was performed in the DAVID database. The protein-protein interaction (PPI) network from the STRING database and the miRNA-target-gene network were merged into a PPI-miRNA network using Cytoscape software. Modules of this network containing miRNAs were detected and further analyzed. Results Ten differentially expressed miRNAs and 1520 target genes were identified. Three PPI-miRNA modules were constructed, which contained miR-424, miR-15a, miR-542-3p, and miR-421 as well as their target genes, CDK1, CDK6, and CCND3. Conclusion The identified miRNAs and genes may be related to the pathogenesis of AF. Thus, they may be potential biomarkers for diagnosis and targets for treatment of AF.

scholarly journals LINC01018 and SMIM25 sponged miR-182-5p in endometriosis revealed by the ceRNA network construction

2020 ◽  
Vol 34 ◽  
pp. 205873842097630
Author(s):  
Li Jiang ◽  
Mengmeng Zhang ◽  
Sixue Wang ◽  
Yuzhen Xiao ◽  
Jingni Wu ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Cerna Network ◽  
Non Coding Rna ◽  
Differentially Expressed Mirnas ◽  
Long Non Coding Rna

The current study intended to explore the interaction of the long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) under the background of competitive endogenous RNA (ceRNA) network in endometriosis (EMs). The differentially expressed miRNAs (DEmiRs), differentially expressed lncRNA (DELs), and differentially expressed genes (DEGs) between EMs ectopic (EC) and eutopic (EU) endometrium based on three RNA-sequencing datasets (GSE105765, GSE121406, and GSE105764) were identified, which were used for the construction of ceRNA network. Then, DEGs in the ceRNA network were performed with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) analysis. Besides, the DEmiRs in the ceRNA network were validated in GSE124010. And the target DELs and DEGs of verified DEmiRs were validated in GSE86534. The correlation of verified DEmiRs, DEGs, and DELs was explored. Moreover, gene set enrichment analysis (GSEA) was applied to investigate the function of verified DEmiRs, DEGs, and DELs. Overall, 1352 DEGs and 595 DELs from GSE105764, along with 27 overlapped DEmiRs between GSE105765 and GSE121406, were obtained. Subsequently, a ceRNA network, including 11 upregulated and 16 downregulated DEmiRs, 7 upregulated and 13 downregulated DELs, 48 upregulated and 46 downregulated DEGs, was constructed. The GO and KEGG pathway analysis showed that this ceRNA network probably was associated with inflammation-related pathways. Furthermore, hsa-miR-182-5p and its target DELs (LINC01018 and SMIM25) and DEGs (BNC2, CHL1, HMCN1, PRDM16) were successfully verified in the validation analysis. Besides, hsa-miR-182-5p was significantly negatively correlated with these target DELs and DEGs. The GSEA analysis implied that high expression of LINC01018, SMIM25, and CHL1, and low expression of hsa-miR-182-5p would activate inflammation-related pathways in endometriosis EU samples. LINC01018 and SMIM25 might sponge hsa-miR-182-5p to upregulate downstream genes such as CHL1 to promote the development of endometriosis.

scholarly journals System Analysis of MIRNAs in Maize Internode Elongation

Biomolecules ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 417
Author(s):  
Chuanxi Peng ◽  
Xing Wang ◽  
Tianyu Feng ◽  
Rui He ◽  
Mingcai Zhang ◽  
...  
Keyword(s):  
Target Genes ◽  
System Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Internode Elongation ◽  
Differentially Expressed Mirnas ◽  
Post Transcriptional Regulation

MicroRNAs (miRNAs), the post-transcriptional gene regulators, are known to play an important role in plant development. The identification of differentially expressed miRNAs could better help us understand the post-transcriptional regulation that occurs during maize internode elongation. Accordingly, we compared the expression of MIRNAs between fixed internode and elongation internode samples and classified six differentially expressed MIRNAs as internode elongation-responsive miRNAs including zma-MIR160c, zma-MIR164b, zma-MIR164c, zma-MIR168a, zma-MIR396f, and zma-MIR398b, which target mRNAs supported by transcriptome sequencing. Functional enrichment analysis for predictive target genes showed that these miRNAs were involved in the development of internode elongation by regulating the genes respond to hormone signaling. To further reveal how miRNA affects internode elongation by affecting target genes, the miRNA–mRNA–PPI (protein and protein interaction) network was constructed to summarize the interaction of miRNAs and these target genes. Our results indicate that miRNAs regulate internode elongation in maize by targeting genes related to cell expansion, cell wall synthesis, transcription, and regulatory factors.

scholarly journals Gene Differential Expression and Interaction Networks Illustrate the Biomarkers and Molecular Mechanisms of Atherosclerotic Cerebral Infarction

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Benzhuo Zhang ◽  
Wei Huang ◽  
Mingquan Yi ◽  
Chunxu Xing
Keyword(s):  
Network Analysis ◽  
Cerebral Infarction ◽  
Antigen Processing ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Neutrophil Activation ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Geo Database

Atherosclerotic cerebral infarction (ACI) seriously threatens the health of the senile patients, and the strategies are urgent for the diagnosis and treatment of ACI. This study investigated the mRNA profiling of the patients with ischemic stroke and atherosclerosis via excavating the datasets in the GEO database and attempted to reveal the biomarkers and molecular mechanism of ACI. In this study, GES16561 and GES100927 were obtained from Gene Expression Omnibus (GEO) database, and the related differentially expressed genes (DEGs) were analyzed with R language. Furthermore, the DEGs were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Besides, the protein-protein interaction (PPI) network of DEGs was analyzed by STRING database and Cytoscape. The results showed that 133 downregulated DEGs and 234 upregulated DEGs were found in GES16561, 25 downregulated DEGs and 104 upregulated DEGs were found in GSE100927, and 6 common genes were found in GES16561 and GES100927. GO enrichment analysis showed that the functional models of the common genes were involved in neutrophil activation, neutrophil degranulation, neutrophil activation, and immune response. KEGG enrichment analysis showed that the DEGs in both GSE100927 and GSE16561 were connected with the pathways including Cell adhesion molecules (CAMs), Cytokine-cytokine receptor interaction, Phagosome, Antigen processing and presentation, and Staphylococcus aureus infection. The PPI network analysis showed that 9 common DEGs were found in GSE100927 and GSE16561, and a cluster with 6 nodes and 12 edges was also identified by PPI network analysis. In conclusion, this study suggested that FCGR3A and MAPK pathways were connected with ACI.

scholarly journals Construction of Circular RNA–MicroRNA–Messenger RNA Regulatory Network of Recurrent Implantation Failure to Explore Its Potential Pathogenesis

2021 ◽  
Vol 11 ◽  
Author(s):  
Jiahuan Luo ◽  
Li Zhu ◽  
Ning Zhou ◽  
Yuanyuan Zhang ◽  
Lirong Zhang ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Implantation Failure ◽  
Ppi Network ◽  
Recurrent Implantation Failure ◽  
Hub Genes ◽  
Hub Gene ◽  
Gene Regulatory

Background: Many studies on circular RNAs (circRNAs) have recently been published. However, the function of circRNAs in recurrent implantation failure (RIF) is unknown and remains to be explored. This study aims to determine the regulatory mechanisms of circRNAs in RIF.Methods: Microarray data of RIF circRNA (GSE147442), microRNA (miRNA; GSE71332), and messenger RNA (mRNA; GSE103465) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed circRNA, miRNA, and mRNA. The circRNA–miRNA–mRNA network was constructed by Cytoscape 3.8.0 software, then the protein–protein interaction (PPI) network was constructed by STRING database, and the hub genes were identified by cytoHubba plug-in. The circRNA–miRNA–hub gene regulatory subnetwork was formed to understand the regulatory axis of hub genes in RIF. Finally, the Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the hub genes were performed by clusterProfiler package of Rstudio software, and Reactome Functional Interaction (FI) plug-in was used for reactome analysis to comprehensively analyze the mechanism of hub genes in RIF.Results: A total of eight upregulated differentially expressed circRNAs (DECs), five downregulated DECs, 56 downregulated differentially expressed miRNAs (DEmiRs), 104 upregulated DEmiRs, 429 upregulated differentially expressed genes (DEGs), and 1,067 downregulated DEGs were identified regarding RIF. The miRNA response elements of 13 DECs were then predicted. Seven overlapping miRNAs were obtained by intersecting the predicted miRNA and DEmiRs. Then, 56 overlapping mRNAs were obtained by intersecting the predicted target mRNAs of seven miRNAs with 1,496 DEGs. The circRNA–miRNA–mRNA network and PPI network were constructed through six circRNAs, seven miRNAs, and 56 mRNAs; and four hub genes (YWHAZ, JAK2, MYH9, and RAP2C) were identified. The circRNA–miRNA–hub gene regulatory subnetwork with nine regulatory axes was formed in RIF. Functional enrichment analysis and reactome analysis showed that these four hub genes were closely related to the biological functions and pathways of RIF.Conclusion: The results of this study provide further understanding of the potential pathogenesis from the perspective of circRNA-related competitive endogenous RNA network in RIF.

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